Most of the optimization techniques in general lead to slow convergence and scant accuracy due to the non-linear behavior of the system. One such nonlinear behavior that acts as a benchmark for control problem is an interacting two-tank system. The two-tank system is a classic example of a control system with a Single Input Single Output (SISO) configuration, where the objective is to regulate the level of water in the second tank by manipulating the flow rate between the two tanks. Meta-heuristic algorithms provide the optimal solution by considering all possible ways for a control problem. In this paper, a modern meta-heuristic optimization algorithm called as Grey Wolf Optimizer (GWO) algorithm is used for obtaining the most feasible solution of a Single Input Single Output (SISO) interacting two-tank system for controlling the liquid level. The GWO algorithm is inspired by the social behavior of grey wolves, which specially focus on their leadership hierarchy as well as in their hunting behavior. GWO algorithm is best suited to obtain the controller parameters to achieve the desired performance in which an optimal solution can be obtained for the effective control of the liquid level in the two-tank system. GWO algorithm is implemented to achieve the desired time integral performance criteria to minimize the integral square error by tracking the set point and disturbances that affects the process. MATLAB SIMULINK software is used to implement the GWO algorithm to optimize the controller parameters of an interacting SISO two tank system